NRT-DESE LUCID: A project-focused cross-disciplinary graduate training program for data-enabled research in human and machine learning and teaching

NRT-DESE LUCID：一个以项目为中心的跨学科研究生培训计划，用于人类和机器学习与教学的数据支持研究

• 批准号: 1545481
• 负责人: Tim Rogers
• 金额: $ 299.98万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1545481&HistoricalAwards=false
• 关键词: NRT; DESE; LUCID; project; focused

NRT DESE: Learning, understanding, cognition, intelligence, and data science (LUCID)In modern life there are many situations requiring people to interact with computers, either so that they may learn from the machine or so that the machine may learn from them. The applications in education, industry, health, robotics, and national security hint at the enormous societal and economic benefits arising from research into the technologies that promote learning in both people and computers. Yet the potential has been difficult to realize because such research requires scientists with expertise in quite different fields of study. While computer scientists receive training in complex computational ideas and methods, they know little about how people learn and behave. This National Science Foundation Research Traineeship (NRT) award to the University of Wisconsin-Madison will prepare trainees with data-enabled science and engineering training to simultaneously understand computational theory and methods, the mechanisms that support human learning and behavior, and the ways these mechanisms behave in complex real-world situations. The traineeship anticipates equipping forty (40) doctoral students with the skills and expertise necessary to advance our understanding of human and machine learning and teaching, through a new training program that focuses on learning, understanding, cognition, intelligence, and data science.This project will train doctoral students from computer science, engineering, cognitive psychology, and education sciences, with the goal of promoting a common knowledge base that allows these scientists to work productively across traditional boundaries on both basic research questions and practical, real-world problems. The traineeship will include several graduate training innovations: (1) a project-focused "prof-and-peer" mentoring system where scientists work in cross-disciplinary teams to address a shared research problem, (2) close involvement of partners in industry, government, and non-profit sectors to develop research problems with real-world application, (3) an information outreach effort that trains scientists to communicate with the public, industry, and policy-makers through traditional and new media outlets, (4) a flexible development plan that allows each trainee to garner the cross-disciplinary expertise needed to advance a particular research focus, and (5) new mechanisms for recruiting and retaining under-represented groups in STEM research. This training will prepare US scientists to compete globally at the highest levels for positions in science, industry, and government, in a growth sector of the 21st century knowledge economy. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, potentially transformative, and scalable models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.This award is supported, in part, by the EHR Core Research (ECR) program, specifically the ECR Research in Disabilities Education (RDE) area of special interest. ECR emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development.

NRT DESE：学习，理解，认知，智能和数据科学（LUCID）在现代生活中，有许多情况需要人们与计算机交互，以便他们可以向机器学习，或者机器可以向他们学习。在教育、工业、健康、机器人和国家安全方面的应用表明，对促进人和计算机学习的技术的研究产生了巨大的社会和经济效益。然而，这种潜力很难实现，因为这样的研究需要在完全不同的研究领域具有专业知识的科学家。虽然计算机科学家在复杂的计算思想和方法方面接受过培训，但他们对人类的学习和行为知之甚少。这项授予威斯康星大学麦迪逊分校的国家科学基金会研究培训（NRT）奖将为受训者提供数据支持的科学和工程培训，以同时理解计算理论和方法，支持人类学习和行为的机制，以及这些机制在复杂的现实世界中的行为方式。通过一个专注于学习、理解、认知、智能和数据科学的新培训项目，该培训计划预计将为40名博士生提供必要的技能和专业知识，以促进我们对人类和机器学习与教学的理解。该项目将培养来自计算机科学、工程学、认知心理学和教育科学的博士生，其目标是促进一个共同的知识库，使这些科学家能够跨越传统的界限，在基础研究问题和实际问题上富有成效地工作。实习将包括几项研究生培训创新：(1)以项目为中心的“教授与同行”指导体系，科学家在跨学科团队中合作解决共同的研究问题；(2)行业、政府和非营利部门的合作伙伴密切参与，开发具有现实应用的研究问题；(3)信息推广工作，培训科学家通过传统和新媒体渠道与公众、行业和政策制定者进行沟通。(4)灵活的发展计划，使每位学员都能获得推进特定研究重点所需的跨学科专业知识；(5)在STEM研究中招募和留住代表性不足群体的新机制。这种培训将使美国科学家在21世纪知识经济的增长领域中，为科学、工业和政府领域的最高水平的职位在全球竞争做好准备。NSF研究培训（NRT）计划旨在鼓励开发和实施大胆的、新的、具有潜在变革性和可扩展的STEM研究生教育培训模式。通过创新、循证、适应不断变化的劳动力和研究需求的综合培训模式，培训项目致力于在高优先级跨学科研究领域对STEM研究生进行有效培训。该奖项在一定程度上得到了EHR核心研究（ECR）项目的支持，特别是ECR残疾教育研究（RDE）领域的特殊利益。ECR强调在STEM领域产生基础知识的基础教育研究。投资在至关重要、广泛和持久的关键领域：STEM学习和STEM学习环境，扩大STEM参与，以及STEM劳动力发展。